
is a point mass, a deterministic not a random function [1]}. Note that for a function to have an inverse, the dimension of \(\epsilon _n\)  should equal the dimension of \(\mathbf {y}_n\) . It could be argued that for variable to be considered a latent variable it needs be an unobserved random variable whose posterior distribution is not degenerate. For example, in the Tobit model [2]}
\(\begin{split}\epsilon _i \sim N(0 ,\sigma ^2)\\y_i^* = \beta x_i +\epsilon _i\\y_i = max(0, y_i^*)\end{split}\) 
